Search results for: Malaysian market error

Authors: Werner Grommes

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Intelligent wearables (illuminated vests or hand and foot-bands, smart watches with a laser diode, Bluetooth smart glasses) overflow the market today. They are integrated with complex electronics and are worn very close to the body. Optical measurements and limitation of the maximum light density are needed. Smart watches are equipped with a laser diode or control different body currents. Special glasses generate readable text information that is received via radio transmission. Small high-performance batteries (lithium-ion/polymer) supply the electronics. All these products have been tested and evaluated for risk. These products must, for example, meet the requirements for electromagnetic compatibility as well as the requirements for electromagnetic fields affecting humans or implant wearers. Extensive analyses and measurements were carried out for this purpose. Many users are not aware of these risks. The result of this study should serve as a suggestion to do it better in the future or simply to point out these risks. Commercial LED warning vests, LED hand and foot-bands, illuminated surfaces with inverter (high voltage), flashlights, smart watches, and Bluetooth smart glasses were checked for risks. The luminance, the electromagnetic emissions in the low-frequency as well as in the high-frequency range, audible noises, and nervous flashing frequencies were checked by measurements and analyzed. Rechargeable lithium-ion or lithium-polymer batteries can burn or explode under special conditions like overheating, overcharging, deep discharge or using out of the temperature specification. Some risk analysis becomes necessary. The result of this study is that many smart wearables are worn very close to the body, and an extensive risk analysis becomes necessary. Wearers of active implants like a pacemaker or implantable cardiac defibrillator must be considered. If the wearable electronics include switching regulators or inverter circuits, active medical implants in the near field can be disturbed. A risk analysis is necessary.

Keywords: safety and hazards, electrical safety, EMC, EMF, active medical implants, optical radiation, illuminated warning vest, electric luminescent, hand and head lamps, LED, e-light, safety batteries, light density, optical glare effects

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Authors: Md Tanvir Rahman, Mahbube Subhani, Mahmud Ashraf, Paul Kremer

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Cross-laminated timber (CLT) is made from layers of timber boards orthogonally oriented in the thickness direction, and due to this, CLT can withstand bi-axial bending in contrast with most other engineered wood products such as laminated veneer lumber (LVL) and glued laminated timber (GLT). Wood is cylindrically anisotropic in nature and is characterized by significantly lower elastic modulus and shear modulus in the planes perpendicular to the fibre direction, and is therefore classified as orthotropic material and is thus characterized by 9 elastic constants which are three elastic modulus in longitudinal direction, tangential direction and radial direction, three shear modulus in longitudinal tangential plane, longitudinal radial plane and radial tangential plane and three Poisson’s ratio. For simplification, timber materials are generally assumed to be transversely isotropic, reducing the number of elastic properties characterizing it to 5, where the longitudinal plane and radial planes are assumed to be planes of symmetry. The validity of this assumption was investigated through numerical modelling of CLT with both orthotropic mechanical properties and transversely isotropic material properties for three softwood species, which are Norway spruce, Douglas fir, Radiata pine, and three hardwood species, namely Victorian ash, Beech wood, and Aspen subjected to uniformly distributed loading under simply supported boundary condition. It was concluded that assuming the timber to be transversely isotropic results in a negligible error in the order of 1 percent. It was also observed that along with longitudinal elastic modulus, ratio of longitudinal shear modulus (GL) and rolling shear modulus (GR) has a significant effect on a deflection for CLT panels of lower span to depth ratio. For softwoods such as Norway spruce and Radiata pine, the ratio of longitudinal shear modulus, GL to rolling shear modulus GR is reported to be in the order of 12 to 15 times in literature. This results in shear flexibility in transverse layers leading to increased deflection under out-of-plane loading. The rolling shear modulus of hardwoods has been found to be significantly higher than those of softwoods, where the ratio between longitudinal shear modulus to rolling shear modulus as low as 4. This has resulted in a significant rise in research into the manufacturing of CLT from entirely from hardwood, as well as from a combination of softwood and hardwoods. The commonly used beam theory to analyze the performance of CLT panels under out-of-plane loads are the Shear analogy method, Gamma method, and k-method. The shear analogy method has been found to be the most effective method where shear deformation is significant. The effect of the ratio of longitudinal shear modulus and rolling shear modulus of cross-layer on the deflection of CLT under uniformly distributed load with respect to its length to depth ratio was investigated using shear analogy method. It was observed that shear deflection is reduced significantly as the ratio of the shear modulus of the longitudinal layer and rolling shear modulus of cross-layer decreases. This indicates that there is significant room for improvement of the bending performance of CLT through developing hybrid CLT from a mix of softwood and hardwood.

Keywords: rolling shear modulus, shear deflection, ratio of shear modulus and rolling shear modulus, timber

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Authors: Praveena Sinha

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Context: Diabetes is a global public health burden, particularly affecting postmenopausal women. Insulin resistance (IR) is prevalent in this population, and it is associated with an increased risk of developing type 2 diabetes. Yoga therapy is gaining attention as a complementary intervention for diabetes due to its potential to address stress psychophysiology. This study focuses on the efficacy of a 12-week yoga practice in attenuating insulin resistance in early postmenopausal women. Research Aim: The aim of this research is to investigate the effect of a 3-month long yoga practice on insulin resistance in early postmenopausal women. Methodology: The study conducted a prospective longitudinal design with 67 women within five years of menopause. Participants were divided into two groups based on their willingness to join yoga. The Yoga group (n = 37) received routine gynecological management along with an integrated yoga module, while the Non-Yoga group (n = 30) received only routine management. Insulin resistance was measured using the homeostasis model assessment of insulin resistance (HOMA-IR) method before and after the intervention. Statistical analysis was performed using GraphPad Prism Version 5 software, with statistical significance set at P < 0.05. Findings: The results indicate a significant decrease in serum fasting insulin levels and HOMA-IR measurements in the Yoga group, although the decrease did not reach statistical significance. In contrast, the Non-Yoga group showed a significant rise in serum fasting insulin levels and HOMA-IR measurements after 3 months, suggesting a detrimental effect on insulin resistance in these postmenopausal women. Theoretical Importance: This study provides evidence that a 12-week yoga practice can attenuate the increase in insulin resistance in early postmenopausal women. It highlights the potential of yoga as a preventive measure against the early onset of insulin resistance and the development of type 2 diabetes mellitus. Regular yoga practice can be a valuable tool in addressing hormonal imbalances associated with early postmenopause, leading to a decrease in morbidity and mortality related to insulin resistance and type 2 diabetes mellitus in this population. Data Collection and Analysis Procedures: Data collection involved measuring serum fasting insulin levels and calculating HOMA-IR. Statistical analysis was performed using GraphPad Prism Version 5 software, and mean values with standard error of the mean were reported. The significance level was set at P < 0.05. Question Addressed: The study aimed to address whether a 3-month long yoga practice could attenuate insulin resistance in early postmenopausal women. Conclusion: The research findings support the efficacy of a 12-week yoga practice in attenuating insulin resistance in early postmenopausal women. Regular yoga practice has the potential to prevent the early onset of insulin resistance and the development of type 2 diabetes mellitus in this population. By addressing the hormonal imbalances associated with early post menopause, yoga could significantly decrease morbidity and mortality related to insulin resistance and type 2 diabetes mellitus in these subjects.

Keywords: post menopause, insulin resistance, HOMA-IR, yoga, type 2 diabetes mellitus

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Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

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Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: electrical disaggregation, DTW, general appliance modeling, event detection

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Authors: Suraj Sam Issaka, Anita Asamoah, Abass Gibrilla, Joseph Richmond Fianko

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Polycyclic aromatic hydrocarbons (PAHs) are a group of organic compounds that can form in edible oils during repeated frying and accumulate in fried foods. This study assesses the chances of health risks (carcinogenic and non-carcinogenic) due to PAHs levels in popular finger foods (bean cakes, plantain chips, doughnuts) fried in edible oils (mixed vegetable, sunflower, soybean) from the Ghanaian market. Employing probabilistic health risk assessment that considers variability and uncertainty in exposure and risk estimates provides a more realistic representation of potential health risks. Monte Carlo simulations with 10,000 iterations were used to estimate carcinogenic, mutagenic, and non-carcinogenic risks for different age groups (A: 6-10 years, B: 11-20 years, C: 20-70 years), food types (bean cake, plantain chips, doughnut), oil types (soybean, mixed vegetable, sunflower), and re-usage frying oil frequencies (once, twice, thrice). Our results suggest that, for age Group A, doughnuts posed the highest probability of carcinogenic risk (91.55%) exceeding the acceptable threshold, followed by bean cakes (43.87%) and plantain chips (7.72%), as well as the highest probability of unacceptable mutagenic risk (89.2%), followed by bean cakes (40.32%). Among age Group B, doughnuts again had the highest probability of exceeding carcinogenic risk limits (51.16%) and mutagenic risk limits (44.27%). At the same time, plantain chips exhibited the highest maximum carcinogenic risk. For adults age Group C, bean cakes had the highest probability of unacceptable carcinogenic (50.88%) and mutagenic risks (46.44%), though plantain chips showed the highest maximum values for both carcinogenic and mutagenic risks in this age group. Also, on non-carcinogenic risks across different age groups, it was found that age Group A) who consumed doughnuts had a 68.16% probability of a hazard quotient (HQ) greater than 1, suggesting potential cognitive impairment and lower IQ scores due to early PAH exposure. This group also faced risks from consuming plantain chips and bean cake. For age Group B, the consumption of plantain chips was associated with a 36.98% probability of HQ greater than 1, indicating a potential risk of reduced lung function. In age Group C, the consumption of plantain chips was linked to a 35.70% probability of HQ greater than 1, suggesting a potential risk of cardiovascular diseases.

Keywords: PAHs, fried foods, carcinogenic risk, non-carcinogenic risk, Monte Carlo simulations

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Authors: Raymond Treacy, Paul Humphreys, Ronan McIvor, Trevor Cadden, Alan McKittrick

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This study employed event study methodology to examine the role of institutions, resources and dynamic capabilities in the relationship between the Environmental Management System ISO 14001 adoption and firm performance. Utilising financial data from 140 ISO 14001 certified firms and 320 non-certified firms, the results of the study suggested that the UK and Irish manufacturers were not implementing ISO 14001 solely to gain legitimacy. In contrast, the results demonstrated that firms were fully integrating the ISO 14001 standard within their operations as certified firms were able to improve both financial and operating performance when compared to non-certified firms. However, while there were significant and long lasting improvements for employee productivity, manufacturing cost efficiency, return on assets and sales turnover, the sample firms operating cycle and fixed asset efficiency displayed evidence of diminishing returns in the long-run, underlying the observation that no operating advantage based on incremental improvements can be everlasting. Hence, there is an argument for investing in dynamic capabilities which help renew and refresh the resource base and help the firm adapt to changing environments. Indeed, the results of the regression analysis suggest that dynamic capabilities for innovation acted as a moderator in the relationship between ISO 14001 certification and firm performance. This, in turn, will have a significant and symbiotic influence on sustainability practices within the participating organisations. The study not only provides new and original insights, but demonstrates pragmatically how firms can take advantage of environmental management systems as a moderator to significantly enhance firm performance. However, while it was shown that firm innovation aided both short term and long term ROA performance, adaptive market capabilities only aided firms in the short-term at the marketing strategy deployment stage. Finally, the results have important implications for firms operating in an economic recession as the results suggest that firms should scale back investment in R&D while operating in an economic downturn. Conversely, under normal trading conditions, consistent and long term investments in R&D was found to moderate the relationship between ISO 14001 certification and firm performance. Hence, the results of the study have important implications for academics and management alike.

Keywords: supply chain management, environmental management systems, quality management, sustainability, firm performance

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Authors: Trude Tørset, María Díez Gutiérrez

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The west coast of Norway features numerous islands and fjords. Ferry services connect the roads when these features make the construction challenging. Currently, scientific effort is designated to assess potential ferry replacement projects along the European road E-39. The inconvenience of ferry dependency is imprecisely represented in the transport models, thus transport analyses of ferry replacement projects appear as guesstimates rather than reliable input to decision-making processes of such costly projects. Trips including ferry connections imply more inconvenient elements than just travel time and cost. The goal of this paper is to understand and explain the extra inconveniences associated to the dependency of the ferry. The first scientific approach is to identify the characteristics of the ferry travelers and their trips’ features, as well as whether the ferry represents an obstacle for some specific trip types. In doing so, a survey was conducted in 2011 in eight E-39 ferries and in 2013 in 18 ferries connecting different road categories. More than 20,000 passengers answered with their trip and socioeconomic characteristics. The travel patterns in the different ferry connections were compared. The analysis showed that the trip features differed based on the location of the ferry connections, yet independently of the road category. Additionally, the patterns were compared to the national travel survey to detect differences in the travel patterns due to the use of the ferry connections. The results showed that the share of commuting trips within the same travel time was lower if the ferry was part of the trip. The second scientific approach is to know how the different travelers perceive potential benefits for a ferry replacement project. In the 2011 survey, some of the questions were about the relevance of nine different benefits this project might bring. Travelers identified the better access to public services and job market as the most valuable benefits, followed by the reduced planning of the trip. In 2016, a follow-up survey in some of the ferry connections was carried out in order to investigate variations in travelers’ perceptions. The growing interest in ferry replacement projects might make travelers more aware of the potential benefits these would bring to their daily lives. This paper describes the travel behaviour of travelers using a ferry connection as part of their trips, as well as the potential inconveniences associated to these trips. The findings might provide valuable input to further development of transport models, concept evaluations and cost benefit analysis methods.

Keywords: ferry connections, ferry trip, inconvenience costs, travel behaviour

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Authors: Gebrehiwot H., Giorgis Bahita

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Firms in Africa experience less financial market in comparison to other emerging and developed countries, thus lagging behind the rest of the world in terms of innovation and growth. Though there are different factors to be considered, underdeveloped financial systems take the lion's share in hindering firm innovation and growth in Africa. Insufficient capacity to innovate is one of the problems facing African businesses. Moreover, a critical challenge faced by firms in Africa is access to finance and the inability of financially constrained firms to grow. Only little is known about how different sources of finance affect firm innovation and growth in Africa, specifically the formal and informal finance effect on firm innovation and growth. This study's aim is to address this gap by using formal and informal finance for working capital and fixed capital and its role in firm innovation and firm growth using firm-level data from the World Bank enterprise survey 2006-2019 with a total of 5661 sample firms from 14 countries based on available data on the selected variables. Additionally, this study examines factors for accessing credit from a formal financial institution. The logit model is used to examine the effect of finance on a firm’s innovation and factors to access formal finance, while the Ordinary List Square (OLS) regression mode is used to investigate the effect of finance on firm growth. 2SLS instrumental variables are used to address the possible endogeneity problem in firm growth and finance-innovation relationships. A result from the logistic regression indicates that both formal and informal finance used for working capital and investment in fixed capital was found to have a significant positive association with product and process innovation. In the case of finance and growth, finding show that positive association of both formal and informal financing to working capital and new investment in fixed capital though the informal has positive relations to firm growth as measured by sale growth but no significant association as measured by employment growth. Formal finance shows more magnitude of effect on innovation and growth when firms use formal finance to finance investment in fixed capital, while informal finance show less compared to formal finance and this confirms previous studies as informal is mainly used for working capital in underdeveloped economies like Africa. The factors that determine credit access: Age, firm size, managerial experience, exporting, gender, and foreign ownership are found to have significant determinant factors in accessing credit from formal and informal sources among the selected sample countries.

Keywords: formal finance, informal finance, innovation, growth

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Authors: Manushi Srivastava

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Introduction: Doctor’s role, and relation with respect to patient care is at the core of medical ethics. The rapid pace of medical advances along with increasing consumer awareness about their rights and hike in cost of effective health care demand a robust, transparent and patient-friendly medical care system. However, doctors’ role performance is still in the frame of activity-passivity model of Doctor-Patient Relationship (DPR) where doctors act as parent and use to instruct their patients, without their consensus that is not going to help in the 21st century. Thus the current situation is a new challenge for traditional doctor-patient relationship after the introduction of Consumer Protection Act (CPA) in medical profession and the same is evidenced by increasing cases of medical litigation. To strengthen this system of medical services, the doctor plays a vital role, and the same should be reviewed in the present context. Objective: To understand the opinion of consultants regarding medical negligence and effect of Consumer Protection Act in terms of current practices of patient care. Method: This is a cross-sectional study in which both quantitative and qualitative methods are applied. Total 69 consultants were selected from multi-specialty hospitals of densely populated Varanasi city catering a population of about 1.8 million. Two-stage sampling was used for selection of respondents. At the first stage, selection of major wards (Medicine, Surgery, Ophthalmology, Gynaecology, Orthopaedics, and Paediatrics) was carried out, which are more susceptible to medical negligence. At the second stage, selection of consultants from the respective wards was carried out. In-depth Interviews were conducted with the help of semi-structured schedule. Two case studies of medical negligence were also carried out as part of the qualitative study. Analysis: Data were analyzed with the help of SPSS software (21.0 trial version). Semi-structured research tool was used to know consultant’s opinion about the pattern of medical negligence cases, litigations and claims made by patient community and inclusion of government medical services in CPA. Statistical analysis was done to describe data, and non-parametric test was used to observe the association between the variables. Analysis of Verbatim was used in case-study. Findings and Conclusion: Majority (92.8%) of consultants felt changes in the behaviour of community (patient) after implementation of CPA, as it had increased awareness about their rights. Less than half of the consultants opined that Medical Negligence is an Unintentional act of doctors and generally occurs due to communication gap and behavioural problem between doctor and patients. Experienced consultants ( > 10 years) pointed out that unethical practice by doctors and mal-intention of patient to harass doctors were additional reasons of Medical Negligence. In-depth interview revealed that now patients’ community expects more transparency and hence they demand cafeteria approach in diagnosis and management of cases. Thus as study results, we propose ‘Agreement Model’ of DPR to re-ensure ethical practice in medical profession.

Keywords: doctors, communication, consumer protection act (CPA), medical error

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Authors: Gaurav Gupta, Jitendra Mahakud

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This study focuses on the significance of internal financing constraints on the determination of corporate fixed investments in the case of Indian manufacturing companies. Financing constraints companies which have less internal fund or retained earnings face more transaction and borrowing costs due to imperfections in the capital market. The period of study is 1999-2000 to 2013-2014 and we consider 618 manufacturing companies for which the continuous data is available throughout the study period. The data is collected from PROWESS data base maintained by Centre for Monitoring Indian Economy Pvt. Ltd. Panel data methods like fixed effect and random effect methods are used for the analysis. The Likelihood Ratio test, Lagrange Multiplier test, and Hausman test results conclude the suitability of the fixed effect model for the estimation. The cash flow and liquidity of the company have been used as the proxies for the internal financial constraints. In accordance with various theories of corporate investments, we consider other firm specific variable like firm age, firm size, profitability, sales and leverage as the control variables in the model. From the econometric analysis, we find internal cash flow and liquidity have the significant and positive impact on the corporate investments. The variables like cost of capital, sales growth and growth opportunities are found to be significantly determining the corporate investments in India, which is consistent with the neoclassical, accelerator and Tobin’s q theory of corporate investment. To check the robustness of results, we divided the sample on the basis of cash flow and liquidity. Firms having cash flow greater than zero are put under one group, and firms with cash flow less than zero are put under another group. Also, the firms are divided on the basis of liquidity following the same approach. We find that the results are robust to both types of companies having positive and negative cash flow and liquidity. The results for other variables are also in the same line as we find for the whole sample. These findings confirm that internal financing constraints play a significant role for determination of corporate investment in India. The findings of this study have the implications for the corporate managers to focus on the projects having higher expected cash inflows to avoid the financing constraints. Apart from that, they should also maintain adequate liquidity to minimize the external financing costs.

Keywords: cash flow, corporate investment, financing constraints, panel data method

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Authors: Sven Borén, Lisiana Nurhadi, Henrik Ny

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From a theoretical perspective, electric buses can be more sustainable and can be cheaper than fossil fuelled buses in city traffic. The authors have not found other studies based on actual urban public transport in Swedish winter climate. Further on, noise measurements from buses for the European market were found old. The aims of this follow-up study was therefore to test and possibly verify in a real-life environment how energy efficient and silent electric buses are, and then conclude on if electric buses are preferable to use in public transport. The Ebusco 2.0 electric bus, fitted with a 311 kWh battery pack, was used and the tests were carried out during November 2014-April 2015 in eight municipalities in the south of Sweden. Six tests took place in urban traffic and two took place in more of a rural traffic setting. The energy use for propulsion was measured via logging of the internal system in the bus and via an external charging meter. The average energy use turned out to be 8% less (0,96 kWh/km) than assumed in the earlier theoretical study. This rate allows for a 320 km range in public urban traffic. The interior of the bus was kept warm by a diesel heater (biodiesel will probably be used in a future operational traffic situation), which used 0,67 kWh/km in January. This verified that electric buses can be up to 25% cheaper when used in public transport in cities for about eight years. The noise was found to be lower, primarily during acceleration, than for buses with combustion engines in urban bus traffic. According to our surveys, most passengers and drivers appreciated the silent and comfortable ride and preferred electric buses rather than combustion engine buses. Bus operators and passenger transport executives were also positive to start using electric buses for public transport. The operators did however point out that procurement processes need to account for eventual risks regarding this new technology, along with personnel education. The study revealed that it is possible to establish a charging infrastructure for almost all studied bus lines. However, design of a charging infrastructure for each municipality requires further investigations, including electric grid capacity analysis, smart location of charging points, and tailored schedules to allow fast charging. In conclusion, electric buses proved to be a preferable alternative for all stakeholders involved in public bus transport in the studied municipalities. However, in order to electric buses to be a prominent support for sustainable development, they need to be charged either by stand-alone units or via an expansion of the electric grid, and the electricity should be made from new renewable sources.

Keywords: sustainability, electric, bus, noise, greencharge

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Authors: Amelia Faotusia

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The blue economy concept was coined by Pacific nations in recognition of the importance of sustainably managing their extensive marine territories. This is especially important for major ocean-based economic sectors of Pacific economies, such as coastal tourism. There is an absence of research, however, on the key ways in which the blue economy concept has emerged in discourse and public policy in Pacific countries, as well as how it articulates with coastal tourism. This research helps to fill such a gap with a specific focus on Tonga through the application of a post-positivist research approach to conduct a desktop study of relevant national documents and qualitative interviews with relevant government staff, civil society organizations, and tourism operators. The findings of the research reflect the importance of institutional integration and partnerships for a successful blue economy transition and are presented in the form of two case studies corresponding to two sub-sectors of Tonga’s coastal tourism sector: (i) the whale-watching and swimming industry, and (ii) beach resorts and restaurants. A thematic analysis applied to the interview data of both cases then enabled the identification of key areas and issues for socio-economic policy intervention and recommendations in support of blue economy transitions in Tonga’s coastal tourism sector. Examples of the relevant areas and issues that emerged included the importance of foreign direct investment, local market access, community-based special management areas, as well as the need to address the anthropogenic impacts of tropical cyclones, whale tourism, plastic litter on coastal assets, and ecosystems. Policy and practical interventions in support of addressing such issues include a proposed restructuring of the whale-watching and swimming licensing system; integration of climate resilience, adaptation, and capacity building as priorities of local blue economy interventions; as well as strengthening of the economic sustainability dimension of blue economy policies. Finally, this research also revealed the need for further specificity and research on the influence and value of local Tongan culture and traditional knowledge, particularly within existing customary marine tenure systems, on Tonga’s national and sectoral blue economy policies and transitions.

Keywords: blue economy, coastal tourism, integrated ocean management, ecosystem resilience

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Authors: Mohammad Ali Hasanzadeh, Thierry Van Elslander, Eddy Van De Voorde

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About 90 percent of world merchandise trade by volume being carried by sea. Maritime transport remains as back bone behind the international trade and globalization meanwhile all seaborne goods need using at least two ports as origin and destination. Amid seaborne traded cargos, container traffic is a prosperous market with about 16% in terms of volume. Albeit containerized cargos are less in terms of tonnage but, containers carry the highest value cargos amongst all. That is why efficient handling of containers in ports is very important. Accidents are the foremost causes that lead to port inefficiency and a surge in total transport cost. Having different port safety management systems (PSMS) in place, statistics on port accidents show that numerous accidents occur in ports. Some of them claim peoples’ life; others damage goods, vessels, port equipment and/or the environment. Several accident investigation illustrate that the most common accidents take place throughout transport operation, it sometimes accounts for 68.6% of all events, therefore providing a safer workplace depends on reducing collision risk. In order to quantify risks at the port area different variables can be used as exposure measurement. One of the main motives for defining and using exposure in studies related to infrastructure is to account for the differences in intensity of use, so as to make comparisons meaningful. In various researches related to handling containers in ports and intermodal terminals, different risk exposures and also the likelihood of each event have been selected. Vehicle collision within the port area (10-7 per kilometer of vehicle distance travelled) and dropping containers from cranes, forklift trucks, or rail mounted gantries (1 x 10-5 per lift) are some examples. According to the objective of the current research, three categories of accidents selected for collision risk assessment; fall of container during ship to shore operation, dropping container during transfer operation and collision between vehicles and objects within terminal area. Later on various consequences, exposure and probability identified for each accident. Hence, reducing collision risks profoundly rely on picking the right risk exposures and probability of selected accidents, to prevent collision accidents in container terminals and in the framework of risk calculations, such risk exposures and probabilities can be useful in assessing the effectiveness of safety programs in ports.

Keywords: container terminal, collision, seaborne trade, risk exposure, risk probability

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Authors: Andrew Gray, Zhibing Zhang

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The ability for consumer products to deliver a sustained perfume response can be a key driver for a variety of applications. Many compounds in perfume oils are highly volatile, meaning they readily evaporate once the product is applied, and the longevity of the scent is poor. Perfume capsules have been introduced as a means of abating this evaporation once the product has been delivered. The impermeable capsules are aimed to be stable within the formulation, and remain intact during delivery to the desired substrate, only rupturing to release the core perfume oil through application of mechanical force applied by the consumer. This opens up the possibility of obtaining an olfactive response hours, weeks or even months after delivery, depending on the nature of the desired application. Tailoring the properties of the polymeric capsules to better address the needs of the application is not a trivial challenge and currently design of capsules is largely done by trial and error. The aim of this work is to have more predictive methods for capsule design depending on the consumer application. This means refining formulations such that they rupture at the right time for the specific consumer application, not too early, not too late. Finding the right balance between these extremes is essential if a benefit is sought with respect to neat addition of perfume to formulations. It is important to understand the forces that influence capsule rupture, first, by quantifying the magnitude of these different forces, and then by assessing bulk rupture in real-world applications to understand how capsules actually respond. Samples were provided by an industrial partner and the mechanical properties of individual capsules within the samples were characterized via a micromanipulation technique, developed by Professor Zhang at the University of Birmingham. The capsules were synthesized such as to change one particular physicochemical property at a time, such as core: wall material ratio, and the average size of capsules. Analysis of shell thickness via Transmission Electron Microscopy, size distribution via the use of a Mastersizer, as well as a variety of other techniques confirmed that only one particular physicochemical property was altered for each sample. The mechanical analysis was subsequently undertaken, showing the effect that changing certain capsule properties had on the response under compression. It was, however, important to link this fundamental mechanical response to capsule performance in real-world applications. As such, the capsule samples were introduced to a formulation and exposed to full scale stresses. GC-MS headspace analysis of the perfume oil released from broken capsules enabled quantification of what the relative strengths of capsules truly means for product performance. Correlations have been found between the mechanical strength of capsule samples and performance in terms of perfume release in consumer applications. Having a better understanding of the key parameters that drive performance benefits the design of future formulations by offering better guidelines on the parameters that can be adjusted without worrying about the performance effects, and singles out those parameters that are essential in finding the sweet spot for capsule performance.

Keywords: consumer products, mechanical and physicochemical properties, perfume capsules, rupture behaviour

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Authors: Tammy Wee, Detlev Remy, Arif Perdana

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In the recent years, data analytics has become the buzzword in the hospitality industry. The hospitality industry is another example of a data-rich industry that has yet fully benefited from the insights of data analytics. Effective use of data analytics can change how hotels operate, market and position themselves competitively in the hospitality industry. However, at the moment, the data obtained by individual hotels remain under-utilized. This research is a preliminary research on data analytics in the hospitality industry, using an in-depth face-to-face interview on one hotel as a start to a multi-level research. The main case study of this research, hotel A, is a chain brand of international hotel that has been systematically gathering and collecting data on its own customer for the past five years. The data collection points begin from the moment a guest book a room until the guest leave the hotel premises, which includes room reservation, spa booking, and catering. Although hotel A has been gathering data intelligence on its customer for some time, they have yet utilized the data to its fullest potential, and they are aware of their limitation as well as the potential of data analytics. Currently, the utilization of data analytics in hotel A is limited in the area of customer service improvement, namely to enhance the personalization of service for each individual customer. Hotel A is able to utilize the data to improve and enhance their service which in turn, encourage repeated customers. According to hotel A, 50% of their guests returned to their hotel, and 70% extended nights because of the personalized service. Apart from using the data analytics for enhancing customer service, hotel A also uses the data in marketing. Hotel A uses the data analytics to predict or forecast the change in consumer behavior and demand, by tracking their guest’s booking preference, payment preference and demand shift between properties. However, hotel A admitted that the data they have been collecting was not fully utilized due to two challenges. The first challenge of using data analytics in hotel A is the data is not clean. At the moment, the data collection of one guest profile is meaningful only for one department in the hotel but meaningless for another department. Cleaning up the data and getting standards correctly for usage by different departments are some of the main concerns of hotel A. The second challenge of using data analytics in hotel A is the non-integral internal system. At the moment, the internal system used by hotel A do not integrate with each other well, limiting the ability to collect data systematically. Hotel A is considering another system to replace the current one for more comprehensive data collection. Hotel proprietors recognized the potential of data analytics as reported in this research, however, the current challenges of implementing a system to collect data come with a cost. This research has identified the current utilization of data analytics and the challenges faced when it comes to implementing data analytics.

Keywords: data analytics, hospitality industry, customer relationship management, hotel marketing

Procedia PDF Downloads 179

Authors: Ting Lu, Ya-Ru Diao, Fei Fan, Ye Xue, Lei Shi, Xian-e Tang, Meng-jun Zhan, Zhen-hua Deng

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Accurate adult age estimation (AAE) is a significant and challenging task in forensic and archeology fields. Attempts have been made to explore optimal adult age metrics, and the rib is considered a potential age marker. The traditional way is to extract age-related features designed by experts from macroscopic or radiological images followed by classification or regression analysis. Those results still have not met the high-level requirements for practice, and the limitation of using feature design and manual extraction methods is loss of information since the features are likely not designed explicitly for extracting information relevant to age. Deep learning (DL) has recently garnered much interest in imaging learning and computer vision. It enables learning features that are important without a prior bias or hypothesis and could be supportive of AAE. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method. Chest CT data were reconstructed using volume rendering (VR). Retrospective data of 2500 patients aged 20.00-69.99 years were obtained between December 2019 and September 2021. Five-fold cross-validation was performed, and datasets were randomly split into training and validation sets in a 4:1 ratio for each fold. Before feeding the inputs into networks, all images were augmented with random rotation and vertical flip, normalized, and resized to 224×224 pixels. ResNeXt was chosen as the DL baseline due to its advantages of higher efficiency and accuracy in image classification. Mean absolute error (MAE) was the primary parameter. Independent data from 100 patients acquired between March and April 2022 were used as a test set. The manual method completely followed the prior study, which reported the lowest MAEs (5.31 in males and 6.72 in females) among similar studies. CT data and VR images were used. The radiation density of the first costal cartilage was recorded using CT data on the workstation. The osseous and calcified projections of the 1 to 7 costal cartilages were scored based on VR images using an eight-stage staging technique. According to the results of the prior study, the optimal models were the decision tree regression model in males and the stepwise multiple linear regression equation in females. Predicted ages of the test set were calculated separately using different models by sex. A total of 2600 patients (training and validation sets, mean age=45.19 years±14.20 [SD]; test set, mean age=46.57±9.66) were evaluated in this study. Of ResNeXt model training, MAEs were obtained with 3.95 in males and 3.65 in females. Based on the test set, DL achieved MAEs of 4.05 in males and 4.54 in females, which were far better than the MAEs of 8.90 and 6.42 respectively, for the manual method. Those results showed that the DL of the ResNeXt model outperformed the manual method in AAE based on CT reconstruction of the costal cartilage and the developed system may be a supportive tool for AAE.

Keywords: forensic anthropology, age determination by the skeleton, costal cartilage, CT, deep learning

Procedia PDF Downloads 73

Authors: Siti Hajar Muhamad Rosli, Xin Yi Lim, Terence Yew Chin Tan, Muhammad nor Farhan Sa’At, Syazwani Sirdar Ali, Ami Fazlin Syed Mohamed

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A growing interest on therapeutic benefits of hemp (Cannabis sativa subsp. sativa) is evident in the pharmaceutical market, attributed to its lower levels of psychoactive constituent delta-9-tetrahydronannabidiol (THC). Deemed as a legal and safer alternative to its counterpart marijuana, the use of medicinal hemp is highly debatable as current scientific evidence on the efficacy for clinical use is yet to be established This study was aimed to provide an overview of the current landscape of hemp research, through recent clinical findings specific to the pharmacological properties of the hemp plant and its derived compounds. A systematic search was conducted following the Preferred Reporting Items for Systematic Review and Meta-Analysis-ScR (PRISMA) checklist on electronic databases (MEDLINE, OVID, Cochrane Library Central, and Clinicaltrials.gov) for articles published from 2009 to 2019. With predetermined inclusion criteria, all human trials with hemp intervention were included. A total of 18 human trials were identified, investigating therapeutic effects on the neuronal, gastrointestinal, musculoskeletal and immune system, with sample sizes ranging from one to 194 subjects. Three randomised controlled trials showed hempseed pills (in Traditional Chinese Medicine formulation MaZiRenWan) consumption significantly improved spontaneous bowel movement in functional constipation. The use of commercial cannabidiol (CBD) sourced from hemp suggested benefits in cannabis dependence, epilepsy, and anxiety disorders. However, there was insufficient evidence to suggest analgesic or anxiolytics effects of hemp being equivalent to marijuana. All clinical trials reviewed varied in terms of test item formulation and standardisation, which made it challenging to confirm overall efficacy for a specific disease or condition. Published efficacy data on hemp are still at a preliminary level, with limited high quality clinical evidence for any specific therapeutic indication. With multiple variants of this plant having different phytochemical and bioactive compounds, future empirical research should focus on uniformity in experimental designs to further strengthen the notion of using medicinal hemp.

Keywords: cannabis, complementary medicine, hemp, herbal medicine.

Procedia PDF Downloads 118

Authors: Mohammad Ghahramani, Fahimeh Saei Manesh

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Winning a soccer game is based on thorough and deep analysis of the ongoing match. On the other hand, giant gambling companies are in vital need of such analysis to reduce their loss against their customers. In this research work, we perform deep, real-time analysis on every soccer match around the world that distinguishes our work from others by focusing on particular seasons, teams and partial analytics. Our contributions are presented in the platform called “Analyst Masters.” First, we introduce various sources of information available for soccer analysis for teams around the world that helped us record live statistical data and information from more than 50,000 soccer matches a year. Our second and main contribution is to introduce our proposed in-play performance evaluation. The third contribution is developing new features from stable soccer matches. The statistics of soccer matches and their odds before and in-play are considered in the image format versus time including the halftime. Local Binary patterns, (LBP) is then employed to extract features from the image. Our analyses reveal incredibly interesting features and rules if a soccer match has reached enough stability. For example, our “8-minute rule” implies if 'Team A' scores a goal and can maintain the result for at least 8 minutes then the match would end in their favor in a stable match. We could also make accurate predictions before the match of scoring less/more than 2.5 goals. We benefit from the Gradient Boosting Trees, GBT, to extract highly related features. Once the features are selected from this pool of data, the Decision trees decide if the match is stable. A stable match is then passed to a post-processing stage to check its properties such as betters’ and punters’ behavior and its statistical data to issue the prediction. The proposed method was trained using 140,000 soccer matches and tested on more than 100,000 samples achieving 98% accuracy to select stable matches. Our database from 240,000 matches shows that one can get over 20% betting profit per month using Analyst Masters. Such consistent profit outperforms human experts and shows the inefficiency of the betting market. Top soccer tipsters achieve 50% accuracy and 8% monthly profit in average only on regional matches. Both our collected database of more than 240,000 soccer matches from 2012 and our algorithm would greatly benefit coaches and punters to get accurate analysis.

Keywords: soccer, analytics, machine learning, database

Procedia PDF Downloads 238

Authors: Ali Kazemi

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The digital evolution of financial services, while offering unprecedented convenience and accessibility, has also escalated the vulnerabilities to fraudulent activities. In this study, we introduce a distinct approach to real-time anomaly detection in financial transactions, aiming to fortify the defenses of banking and financial institutions against such threats. Utilizing unsupervised machine learning algorithms, specifically autoencoders and isolation forests, our research focuses on identifying irregular patterns indicative of fraud within transactional data, thus enabling immediate action to prevent financial loss. The data we used in this study included the monetary value of each transaction. This is a crucial feature as fraudulent transactions may have distributions of different amounts than legitimate ones, such as timestamps indicating when transactions occurred. Analyzing transactions' temporal patterns can reveal anomalies (e.g., unusual activity in the middle of the night). Also, the sector or category of the merchant where the transaction occurred, such as retail, groceries, online services, etc. Specific categories may be more prone to fraud. Moreover, the type of payment used (e.g., credit, debit, online payment systems). Different payment methods have varying risk levels associated with fraud. This dataset, anonymized to ensure privacy, reflects a wide array of transactions typical of a global banking institution, ranging from small-scale retail purchases to large wire transfers, embodying the diverse nature of potentially fraudulent activities. By engineering features that capture the essence of transactions, including normalized amounts and encoded categorical variables, we tailor our data to enhance model sensitivity to anomalies. The autoencoder model leverages its reconstruction error mechanism to flag transactions that deviate significantly from the learned normal pattern, while the isolation forest identifies anomalies based on their susceptibility to isolation from the dataset's majority. Our experimental results, validated through techniques such as k-fold cross-validation, are evaluated using precision, recall, and the F1 score alongside the area under the receiver operating characteristic (ROC) curve. Our models achieved an F1 score of 0.85 and a ROC AUC of 0.93, indicating high accuracy in detecting fraudulent transactions without excessive false positives. This study contributes to the academic discourse on financial fraud detection and provides a practical framework for banking institutions seeking to implement real-time anomaly detection systems. By demonstrating the effectiveness of unsupervised learning techniques in a real-world context, our research offers a pathway to significantly reduce the incidence of financial fraud, thereby enhancing the security and trustworthiness of digital financial services.

Keywords: anomaly detection, financial fraud, machine learning, autoencoders, isolation forest, transactional data analysis

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Authors: A. G. Back

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In the context of global climate change, extreme weather events are increasingly intense and frequent, challenging the adaptability of urban space. In this sense, urban planning is a relevant instrument for addressing, in a systemic manner, various sectoral policies capable of linking the urban agenda to the reduction of social and environmental risks. The Master Plan of the Municipality of Sao Paulo, 2014, presents innovations capable of promoting the transition to sustainability in the urban space. Among such innovations, the following stand out: i) promotion of density in the axes of mass transport involving mixture of commercial, residential, services, and leisure uses (principles related to the compact city); ii) vulnerabilities reduction based on housing policies, including regular sources of funds for social housing and land reservation in urbanized areas; iii) reserve of green areas in the city to create parks and environmental regulations for new buildings focused on reducing the effects of heat island and improving urban drainage. However, long-term implementation involves distributive conflicts and may change in different political, economic, and social contexts over time. Thus, the central objective of this paper is to identify which factors limit or support the implementation of these policies. That is, to map the challenges and interests of converging and/or divergent urban actors in the sustainable urban development agenda and what resources they mobilize to support or limit these actions in the city of Sao Paulo. Recent proposals to amend the urban zoning law undermine the implementation of the Master Plan guidelines. In this context, three interest groups with different views of the city come into dispute: the real estate market, upper middle class neighborhood associations ('not in my backyard' movements), and social housing rights movements. This paper surveys the different interests and visions of these groups taking into account their convergences, or not, with the principles of sustainable urban development. This approach seeks to fill a gap in the international literature on the causes that underpin or hinder the continued implementation of policies aimed at the transition to urban sustainability in the medium and long term.

Keywords: adaptation, ecosystem-based adaptation, interest groups, urban planning, urban transition to sustainability

Procedia PDF Downloads 121

Authors: Frezer Okubay Weldegebriel

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The tourism sector in Ethiopia plays a significant role in the national economy. The government is granting its pledge and readiness to develop this sector through various initiatives since to eradicate poverty and encourage economic development of the country is one of the Millennium Development plans. The tourism sector has been identified as one of the priority economic sectors by many countries, and the Government of Ethiopia has planned to make Ethiopia among the top five African destinations by 2020. Nevertheless, the international tourism demand for Ethiopia currently lags behind other African countries such as South Africa, Egypt, Morocco, Tanzania, and Kenya. Meanwhile, the number of international tourists’ arrival in Ethiopia is recently increasing even if it cannot be competitive with other African countries. Therefore, to offer demand-driven tourism products, the Ethiopian government, Tourism planners, Tour & Travel operators need to understand the important factors, which affect international tourists’ decision to visit Ethiopian destinations. This study was intended to analyze Italian Tourists Demand towards Ethiopian destination. The researcher aimed to identify the demand for Italian tourists’ preference to Ethiopian destinations comparing to the top East African countries. This study uses both qualitative and quantitative research methodology, and the data is manipulating through primary data collection method using questionnaires, interviews, and secondary data by reviewing books, journals, magazines, past researches, and websites. An active and potential Italian tourist cohort, five well-functioning tour operators based in Ethiopia for Italian tourists and professionals from Ethiopian Ministry of Tourism and Culture participated. Based on the analysis of the data collected through the questionnaire, interviews, and reviews of different materials, the study disclosed that the majority of Italian tourists have a high demand on Ethiopian Tourist destination. Historical and cultural interest, safety and security, the hospitality of the people and affordable accommodation coast are the main reason for them. However, some Italian tourists prefer to visit Kenya, Tanzania, and Uganda due to the fact that they are fascinated by adventure, safari and beaches, while Ethiopia cannot provide these attractions. Most Italian tourists have little information and practical experiences on Ethiopian tourism possibilities via a tour and travel companies. Moreover, the insufficient marketing campaign and promotion by Ethiopian Government and Ministry of Tourism could also contribute to the failure of Ethiopian tourism.

Keywords: The demand of Italian tourists, Ethiopia economy, Ethiopia tourism destination, promoting Ethiopia tourism

Procedia PDF Downloads 208

Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

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Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: general appliance model, non intrusive load monitoring, events detection, unsupervised techniques;

Procedia PDF Downloads 82

Authors: Dipak Subedi, Anil Giri, Christine Whitt, Tia McDonald

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This study aims to understand the impact of the pandemic on the overall economic well-being of the agricultural sector of the United States. The two key metrics used to examine the economic well-being are the bankruptcy rate of the U.S. farm operations and the operating profit margin. One of the primary reasons for farm operations (in the U.S.) to file for bankruptcy is continuous negative profit or a significant decrease in profit. The pandemic caused significant supply and demand shocks in the domestic market. Furthermore, the ongoing trade disruptions, especially with China, also impacted the prices of agricultural commodities. The significantly reduced demand for ethanol and closure of meat processing plants affected both livestock and crop producers. This study uses data from courts to examine the bankruptcy rate over time of U.S. farm operations. Preliminary results suggest there wasn’t an increase in farm operations filing for bankruptcy in 2020. This was most likely because of record high Government payments to producers in 2020. The Federal Government made direct payments of more than $45 billion in 2020. One commonly used economic metric to measure farm profitability is the operating profit margin (OPM). Operating profit margin measures profitability as a share of the total value of production and government payments. The Economic Research Service of the United States Department of Agriculture defines a farm operation to be in a) a high-risk zone if the OPM is less than 10 percent and b) a low-risk zone if the OPM is higher than 25 percent. For this study, OPM was calculated for small, medium, and large-scale farm operations using the data from the Agriculture Resource Management Survey (OPM). Results show that except for small family farms, the share of farms in high-risk zone decreased in 2020 compared to the most recent non-pandemic year, 2019. This was most likely due to higher commodity prices at the end of 2020 and record-high government payments. Further investigation suggests a lower share of smaller farm operations receiving lower average government payments resulting in a large share (over 70 percent) being in the critical zone. This study should be of interest to multiple stakeholders, including policymakers across the globe, as it shows the resilience of the U.S. agricultural system as well as (some) impact of government payments.

Keywords: U.S. farm sector, COVID-19, operating profit margin, farm bankruptcy, ag finance, government payments to the farm sector

Procedia PDF Downloads 88

Authors: Lenka Krsnakova, Petr Jirsak

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Prior research on facility location in supply chain is mostly focused on improvement of mathematical models. It is due to the fact that supply chain design has been for the long time the area of operational research that underscores mainly quantitative criteria. Qualitative criteria are still highly neglected within the supply chain design research. Facility location in the supply chain has become multi-criteria decision-making problem rather than single criteria decision due to changes of market conditions. Thus, both qualitative and quantitative criteria have to be included in the decision making process. The aim of this study is to emphasize the importance of qualitative criteria as key parameters of relevant mathematical models. We examine which criteria are taken into consideration when Czech companies decide about their facility location. A literature review on criteria being used in facility location decision making process creates a theoretical background for the study. The data collection was conducted through questionnaire survey. Questionnaire was sent to manufacturing and business companies of all sizes (small, medium and large enterprises) with the representation in the Czech Republic within following sectors: automotive, toys, clothing industry, electronics and pharmaceutical industry. Comparison of which criteria prevail in the current research and which are considered important by companies in the Czech Republic is made. Despite the number of articles focused on supply chain design, only minority of them consider qualitative criteria and rarely process supply chain design as a multi-criteria decision making problem. Preliminary results of the questionnaire survey outlines that companies in the Czech Republic see the qualitative criteria and their impact on facility location decision as crucial. Qualitative criteria as company strategy, quality of working environment or future development expectations are confirmed to be considered by Czech companies. This study confirms that the qualitative criteria can significantly influence whether a particular location could or could not be right place for a logistic facility. The research has two major limitations: researchers who focus on improving of mathematical models mostly do not mention criteria that enter the model. Czech supply chain managers selected important criteria from the group of 18 available criteria and assign them importance weights. It does not necessarily mean that these criteria were taken into consideration when the last facility location was chosen, but how they perceive that today. Since the study confirmed the necessity of future research on how qualitative criteria influence decision making process about facility location, the authors have already started in-depth interviews with participating companies to reveal how the inclusion of qualitative criteria into decision making process about facility location influence the company´s performance.

Keywords: criteria influencing facility location, Czech Republic, facility location decision-making, qualitative criteria

Procedia PDF Downloads 324

Authors: Fernando Nobre Cavalcante

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In Brazil, and more recently in the city of Fortaleza, there is a new form of entrepreneurship that is focused on the information and communication technology service sector and that draws the attention of young people, investors, governments, authors and media companies: it is known as the start-up movement. Today, it is considered to be a driving force behind the creative economy. Rooted on progressive discourse, the words enterprise and innovation seduce new economic agents motivated by success stories from Silicon Valley in America along with increasing commercial activity for digital goods and services. This article assesses, from a sociological point of view, the new productive wave problematized by the light of Manuel Castells’ informational capitalism. Considering the skeptical as well as the optimistic opinions about the impact of this new entrepreneurial rearrangement, the following question is asked: How Brazilian entrepreneurs evaluate public policy incentives for startups Brazilian Federal Government? The raised hypotheses are based on employability factors as well as cultural, economical, and political matters related to innovation and technology. This study has produced a nationwide quantitative assessment with a special focus on the reality of these Ceará firms; as well as comparative qualitative interviews on Brazilian experiences lived by identified agents. This article outlines the public incentive policy of the federal government, the Start-up Brasil Program, from the perspective of these companies and provides details as to the discipline methods of the new enterprising way born in the United States. The startups are very young companies that are headed towards the economic sustainment of the productive sector services. These companies are dropping the seeds that will produce the re-enchantment of young people and bring them back to participation in political debate; they provide relief and reheats the job market; and they produce a democratization of the entrepreneurial ‘Do-It-Yourself’ culture. They capitalize the pivot of the wall street wolves and of agents being charged for new masks. There are developmental logic’s prophylaxis in the face of dreadful innovation stagnation. The lack of continuity in Brazilian governmental politics and cultural nuances related to entrepreneurship are barring the desired regional success of this ecosystem.

Keywords: creative economy, entrepreneurship, informationalism, innovation, startups, start-up brasil program

Procedia PDF Downloads 368

Authors: Giovanni Duran Polo

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Demonstrate the importance of the stages such as Information, Diagnosis, Management, and Intervention is fundamental to have a historical, live, and quality inhabited center. One of the major actions to take is to promote the concept of the management of a historic center with harmonious development. For that, concerned actors should strengthen the concept that said historic center may be the neighborhood of all and for all. The centers of historical cities, presented as any other urban area, social, environmental issues etc; yet they get added value that have no other city neighborhoods. The equity component, either by the urban plan, or environmental quality offered properties of architectural, landscape or some land uses are the differentiating element, while the tool that makes them attractive face pressure exerted by new housing developments or shopping centers. That's why through the experience of working in historical centers, they are declared the actions in heritage areas. This paper will show how the encounter with each of these places are trying to take the phases of information, to gather all the data needed to be closer to the territory with specific data, diagnosis; which allowed the actors to see what state they were, felt how the heart is related to the rest of the city, show what problems affected the situation and what potential it had to compete in a global market. Also, to discuss the importance of the organization, as it is legal and normative basis for it have an order and a concept, when you know what can and what cannot, in an area where the citizen has many myth or history, when he wanted to intervene in protected buildings. It is also appropriate to show how it could develop the intervention phase, where the shares on the tangible elements and intervention for the protection of the heritage property are executed. The management is the final phase which will carry out all that was raised on paper, it's time to orient, explain, persuade, promote, and encourage citizens to take care of the heritage. It is profitable and also an obligation and it is not an insurmountable burden. It has to be said this is the time to pull all the cards to make the historical center and heritage becoming more alive today. It is the moment to make it more inhabited and to transformer it into a quality place, so citizens will cherish and understand the importance of such a place. Inhabited historical centers, endowments and equipment required, with trade quality, with constant cultural offer, with well-preserved buildings and tidy, modern and safe public spaces are always attractive for tourism, but first of all, the place should be conceived for citizens, otherwise everything will be doomed to failure.

Keywords: development, diagnosis, heritage historic center, intervention, management, patrimony

Procedia PDF Downloads 395

Authors: Raja Umer Sajjad, Chang Hee Lee

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Stormwater runoff is the leading contributor to pollution of receiving waters. In response, an efficient stormwater monitoring program is required to quantify and eventually reduce stormwater pollution. The overall goals of stormwater monitoring programs primarily include the identification of high-risk dischargers and the development of total maximum daily loads (TMDLs). The challenge in developing better monitoring program is to reduce the variability in flux estimates due to sampling errors; however, the success of monitoring program mainly depends on the accuracy of the estimates. Apart from sampling errors, manpower and budgetary constraints also influence the quality of the estimates. This study attempted to develop optimum stormwater monitoring design considering both cost and the quality of the estimated pollutants flux. Three years stormwater monitoring data (2012 – 2014) from a mix land use located within Geumhak watershed South Korea was evaluated. The regional climate is humid and precipitation is usually well distributed through the year. The investigation of a large number of water quality parameters is time-consuming and resource intensive. In order to identify a suite of easy-to-measure parameters to act as a surrogate, Principal Component Analysis (PCA) was applied. Means, standard deviations, coefficient of variation (CV) and other simple statistics were performed using multivariate statistical analysis software SPSS 22.0. The implication of sampling time on monitoring results, number of samples required during the storm event and impact of seasonal first flush were also identified. Based on the observations derived from the PCA biplot and the correlation matrix, total suspended solids (TSS) was identified as a potential surrogate for turbidity, total phosphorus and for heavy metals like lead, chromium, and copper whereas, Chemical Oxygen Demand (COD) was identified as surrogate for organic matter. The CV among different monitored water quality parameters were found higher (ranged from 3.8 to 15.5). It suggests that use of grab sampling design to estimate the mass emission rates in the study area can lead to errors due to large variability. TSS discharge load calculation error was found only 2 % with two different sample size approaches; i.e. 17 samples per storm event and equally distributed 6 samples per storm event. Both seasonal first flush and event first flush phenomena for most water quality parameters were observed in the study area. Samples taken at the initial stage of storm event generally overestimate the mass emissions; however, it was found that collecting a grab sample after initial hour of storm event more closely approximates the mean concentration of the event. It was concluded that site and regional climate specific interventions can be made to optimize the stormwater monitoring program in order to make it more effective and economical.

Keywords: first flush, pollutant load, stormwater monitoring, surrogate parameters

Procedia PDF Downloads 240

Authors: Nabeeha Hassan Abdel Jalil, Lulwa Saeed Al Badi, Mouza Ghafan Alkhyeli, Khaja Mohteshamuddin, Ahmad Al Aiyan, Mohamed Elfatih Hamad, Robert Barigye

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The present study was done to elucidate the prevalence of enzootic bovine leucosis (EBL) in the UAE, the seroprevalence rates of EBL in dairy herds from the Al Ain area, Abu Dhabi (AD) and indigenous cattle at the Al Ain livestock market (AALM) were assessed. Of the 949 sera tested by ELISA, 657 were from adult Holstein-Friesians from three farms and 292 from indigenous cattle at the AALM. The level of significance between the proportions of seropositive cattle were analyzed by the Marascuilo procedure and questionnaire data on husbandry and biosecurity practices evaluated. Overall, the aggregated farm and AALM data demonstrated a seroprevalence of 25.9%, compared to 37.0% for the study farms, and 1.0% for the indigenous cattle. Additionally, the seroprevalence rates at farms #1, #2 and #3 were 54.7%, 0.0%, and 26.3% respectively. Except for farm #2 and the AALM, statistically significant differences were noted between the proportions of seropositive cattle for farms #1 and #2 (Critical Range or CR=0.0803), farms #1 and #3 (p=0.1069), and farms #2 and #3 (CR=0.0707), farm #1 and the AALM (CR=0.0819), and farm #3 and the AALM (CR=0.0726). Also, the proportions of seropositive animals on farm #1 were 9.8%, 59.8%, 29.3%, and 1.2% in the 12-36, 37-72, 73-108, and 109-144-mo-old age groups respectively compared to 21.5%, 60.8%, 15.2%, and 2.5% in the respective age groups for farm #2. On both farms and the AALM, the 37-72-mo-old age group showed the highest EBL seroprevalence rate while all the 57 cattle on farm #2 were seronegative. Additionally, farms #1 and #3 had 3,130 and 2,828 intensively managed Holstein-Friesian cattle respectively, and all animals were routinely immunized against several diseases except EBL. On both farms #1 and #3, artificial breeding was practiced using semen sourced from the USA, and USA and Canada respectively, all farms routinely quarantined new stock, and farm #1 previously imported dairy cattle from an unspecified country, and farm #3 from the Netherlands, Australia and South Africa. While farm #1 provided no information on animal nutrition, farm #3 cited using hay, concentrates, and ad lib water. To the authors’ best knowledge, this is the first serological evidence of EBL in the UAE and as previously reported, the seroprevalence rates are comparatively higher in the intensively managed dairy herds than in indigenous cattle. As two of the study farms previously sourced cattle and semen from overseas, biosecurity protocols need to be revisited to avoid inadvertent EBL incursion and the possibility of regional transboundary disease spread also needs to be assessed. After the proposed molecular studies have adduced additional data, the relevant UAE animal health authorities may need to develop evidence-based EBL control policies and programs.

Keywords: cattle, enzootic bovine leukosis, seroprevalence, UAE

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Authors: A.H.Y. Lai, C. Teyra

Abstract:

In Taiwan, there are 16 official indigenous groups, accounting for 2.3% of the total population. Like other indigenous populations worldwide, indigenous peoples in Taiwan have poorer mental health because of their history of oppression and colonisation. Amid the negative narratives, the ethnic identity of cultural minorities is their unique psychological and cultural asset. Moreover, positive socialisation is found to be related to strong ethnic identity. Based on Phinney’s theory on ethnic identity development and social support theory, this study adopted a strength-based approach conceptualising ethnic identity as the central organising principle that linked perceived social support and mental health among indigenous adults in Taiwan. Aims. Overall aim is to examine the effect of ethnic identity and social support on mental health. Specific aims were to examine : (1) the association between ethnic identity and mental health; (2) the association between perceived social support and mental health ; (3) the indirect effect of ethnic identity linking perceived social support and mental health. Methods. Participants were indigenous adults in Taiwan (n=200; mean age=29.51; Female=31%, Male=61%, Others=8%). A cross-sectional quantitative design was implemented using data collected in the year 2020. Respondent-driven sampling was used. Standardised measurements were: Ethnic Identity Scale(6-item); Social Support Questionnaire-SF(6 items); Patient Health Questionnaire(9-item); and Generalised Anxiety Disorder(7-item). Covariates were age, gender and economic satisfaction. A four-stage structural equation modelling (SEM) with robust maximin likelihood estimation was employed using Mplus8.0. Step 1: A measurement model was built and tested using confirmatory factor analysis (CFA). Step 2: Factor covariates were re-specified as direct effects in the SEM. Covariates were added. The direct effects of (1) ethnic identity and social support on depression and anxiety and (2) social support on ethnic identity were tested. The indirect effect of ethnic identity was examined with the bootstrapping technique. Results. The CFA model showed satisfactory fit statistics: x^2(df)=869.69(608), p<.05; Comparative ft index (CFI)/ Tucker-Lewis fit index (TLI)=0.95/0.94; root mean square error of approximation (RMSEA)=0.05; Standardized Root Mean Squared Residual (SRMR)=0.05. Ethnic identity is represented by two latent factors: ethnic identity-commitment and ethnic identity-exploration. Depression, anxiety and social support are single-factor latent variables. For the SEM, model fit statistics were: x^2(df)=779.26(527), p<.05; CFI/TLI=0.94/0.93; RMSEA=0.05; SRMR=0.05. Ethnic identity-commitment (b=-0.30) and social support (b=-0.33) had direct negative effects on depression, but ethnic identity-exploration did not. Ethnic identity-commitment (b=-0.43) and social support (b=-0.31) had direct negative effects on anxiety, while identity-exploration (b=0.24) demonstrated a positive effect. Social support had direct positive effects on ethnic identity-exploration (b=0.26) and ethnic identity-commitment (b=0.31). Mediation analysis demonstrated the indirect effect of ethnic identity-commitment linking social support and depression (b=0.22). Implications: Results underscore the role of social support in preventing depression via ethnic identity commitment among indigenous adults in Taiwan. Adopting the strength-based approach, mental health practitioners can mobilise indigenous peoples’ commitment to their group to promote their well-being.

Keywords: ethnic identity, indigenous population, mental health, perceived social support

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Authors: Mojtaba Taheri, Saied Reza Ameli

Abstract:

In this research, we have calculated the effect of membership in international climate change treaties for 20 developed countries based on the human development index (HDI) and compared this effect with the process of pollutant reduction in the Environmental Kuznets Curve (EKC) theory. For this purpose, the data related to The real GDP per capita with 2010 constant prices is selected from the World Development Indicators (WDI) database. Ecological Footprint (ECOFP) is the amount of biologically productive land needed to meet human needs and absorb carbon dioxide emissions. It is measured in global hectares (gha), and the data retrieved from the Global Ecological Footprint (2021) database will be used, and we will proceed by examining step by step and performing several series of targeted statistical regressions. We will examine the effects of different control variables, including Energy Consumption Structure (ECS) will be counted as the share of fossil fuel consumption in total energy consumption and will be extracted from The United States Energy Information Administration (EIA) (2021) database. Energy Production (EP) refers to the total production of primary energy by all energy-producing enterprises in one country at a specific time. It is a comprehensive indicator that shows the capacity of energy production in the country, and the data for its 2021 version, like the Energy Consumption Structure, is obtained from (EIA). Financial development (FND) is defined as the ratio of private credit to GDP, and to some extent based on the stock market value, also as a ratio to GDP, and is taken from the (WDI) 2021 version. Trade Openness (TRD) is the sum of exports and imports of goods and services measured as a share of GDP, and we use the (WDI) data (2021) version. Urbanization (URB) is defined as the share of the urban population in the total population, and for this data, we used the (WDI) data source (2021) version. The descriptive statistics of all the investigated variables are presented in the results section. Related to the theories of sustainable development, Environmental Kuznets Curve (EKC) is more significant in the period of study. In this research, we use more than fourteen targeted statistical regressions to purify the net effects of each of the approaches and examine the results.

Keywords: climate change, globalization, environmental economics, sustainable development, international climate treaty

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